code: def testPNAGNN():
      import dgl
      from deepchem.models.torch_models.pna_gnn import PNAGNN
  
      data, _ = get_regression_dataset()
      features = dgl.batch(
          [conformer.to_dgl_graph() for conformer in data.X]
      )
      model = PNAGNN(
          hidden_dim=16,
          aggregators=["mean", "sum"],
          scalers=["identity"],
      )
      output = model(features)
  
      assert output.ndata["feat"].shape == (
          features.ndata["x"].shape[0],
          16,
      )
  
file_path: deepchem/deepchem/models/tests/test_pna.py
imports: import os
  import numpy
  import deepchem
  import pytest
label_desc: Use image node_id 5 for calling a global function with example usage: testPNAGNN() without return types